Results for “llamaindex”
11 skills
agentskillexchange Llamaindex Agent
Builds RAG and agent applications with LlamaIndex, covering installation, LlamaParse, and LlamaAgents.
28
orchestra-research Llamaindex
Connects LLMs with user data for RAG applications, document Q&A, and knowledge retrieval using 300+ data connectors and vector indices.
10.4k · bundle
lord1egypt Faiss
Enables fast similarity search and clustering of dense vectors using FAISS, covering index types, GPU acceleration, and integrations with LangChain and LlamaIndex.
2
lord1egypt Chroma
Store and query embeddings with metadata, vector and full-text search, and filtering. Integrates with LangChain and LlamaIndex for RAG and semantic search applications.
2
lord1egypt Qdrant Vector Search
Builds production RAG and semantic search systems with Qdrant, covering collection setup, vector indexing, filtered and hybrid search, and integration with LangChain and LlamaIndex.
2
More results
orchestra-research Faiss
Enables fast similarity search and clustering of dense vectors using FAISS, supporting billions of vectors, GPU acceleration, and various index types.
10.4k · bundle
orchestra-research Pinecone
Provides code examples and best practices for using Pinecone, a managed vector database for production RAG, recommendation, and semantic search applications.
10.4k · bundle
orchestra-research Chroma
Store and query embeddings with metadata filtering, vector search, and full-text search using an open-source database that scales from notebooks to production.
10.4k · bundle
mariadb-corporation Mariadb Vector
Provides best practices for using MariaDB's built-in vector support for AI workloads, including SQL syntax for vector columns, indexes, distance functions, and RAG patterns.
0
orchestra-research Qdrant Vector Search
Build production RAG and semantic search systems with a high-performance vector database written in Rust, supporting hybrid search, filtering, and horizontal scaling.
10.4k · bundle
orchestra-research Sentence Transformers
Generate high-quality sentence and text embeddings for semantic similarity, clustering, and retrieval using 5000+ pre-trained models. Supports multilingual and domain-specific embeddings for RAG and semantic search.
10.4k · bundle